AtScale Adaptive Analytics (A3) vs Google Data Studio comparison

The compared AtScale and Google solutions aren't in the same category. AtScale is ranked #7 in DV , and holds a 6.1% mindshare in the category. Google is ranked #8 in EBT , with an average rating of 8.0, and holds a 5.5% mindshare. Additionally, 80% of Google users are willing to recommend the solution.

AtScale Adaptive Analytics ...

Read 1 AtScale Adaptive Analytics (A3) review

1,644 Views
181 Comparison Views

0% willing to recommend

Google Data Studio

Read 20 Google Data Studio reviews

3,253 Views
1,464 Comparison Views

80% willing to recommend

AtScale Adaptive Analytics ...

Google Data Studio

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

AtScale Adaptive Analytics ...

Average Rating

5.0

Number of Reviews

Ranking in other categories

Data Virtualization (7th), BI (Business Intelligence) Tools (50th), Data Governance (45th), BI on Hadoop (1st)

Google Data Studio

Average Rating

8.0

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

Embedded BI (8th)

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. AtScale Adaptive Analytics (A3) is designed for Data Virtualization and holds a mindshare of 6.1%, down 8.7% compared to last year.
Google Data Studio, on the other hand, focuses on Embedded BI, holds 5.5% mindshare, down 9.4% since last year.

Data Virtualization Mindshare Distribution
Product	Mindshare (%)
AtScale Adaptive Analytics (A3)	6.1%
Denodo	22.1%
TIBCO Data Virtualization	15.0%
Other	56.8%

Data Virtualization

Embedded BI Mindshare Distribution
Product	Mindshare (%)
Google Data Studio	5.5%
Tableau Enterprise	17.5%
Qlik Sense	7.9%
Other	69.1%

Embedded BI

Featured Reviews

it_user822762

Senior BI and Reporting Analyst at a financial services firm with 10,001+ employees

The GUI interface is nice and easy to use, but the organization of the icons is not saved across users

Connecting to a Hadoop database to create a cube to connect to Tableau. We want to be able to easily create cubes which can be connected to Tableau for visualization The product had many issues. We had great collaboration with the product development team, but the product was not able to meet our…

Read full review

Hemanthreddy Vakiti

Data engineer at a tech vendor with 10,001+ employees

Automated dashboards have transformed daily trend analysis and now drive faster business decisions

One of the best features that Looker offers is LookML, which allows us to develop dashboards directly rather than dragging and dropping. We can also customize some fields that are not available in the table by combining different tables using LookML. Compared to other reporting tools, Looker is somewhat more customizable and interactive. With the help of Views and Explore in Looker, we can combine different tables and create a unique column that is not available in the table, and then use that column in our reporting dashboard. Since we brought Looker into our project, it has improved data visibility and enabled faster interaction between us and our client. Rather than simply using free form or Essbase, seeing customizable and visualized data in Looker allows the business users to understand the trends in the data more easily rather than just seeing numbers. It has helped us save a lot of time. The automated dashboards that we develop allow us to run the dashboard for the coming years with only some modifications, which has reduced some manpower and working hours. When I joined this project, there were around eight to nine people for developing Looker dashboards. Once the development part is completed for almost all cases, the next part is just monitoring the dashboards and making some minor changes required to align with business goals. After development, the team was reduced to three or four people, so the manpower has significantly reduced, and time taken has decreased as well. For a business user to understand data from free form or Essbase, it usually takes thirty minutes to an hour to go through the previous day's trend. However, with the visualization tools in Looker, they can easily understand the data and compare it to the previous one or two years using a bar graph, pie chart, or other graphs. The return on investment has been very good. The number of employees has reduced to half, and time is saved by nearly two to three hours a day because of automated reports. We are just monitoring the reports to ensure they are released. This has saved nearly two hours per day, and the team has been reduced to half.

Read full review

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The GUI interface is nice and easy to use."

"I would rate the stability a ten out of ten. I didn't face any issues with stability."

"Looker allows you to generate the most optimal SQL queries in a DC through UI actions. We had signed a contract with Google Cloud to use BigQuery. That was the primary reason we adopted Looker. It works better with BigQuery than any other BI platform. We also like how this tool was developed. It was designed with an eye toward microservices architecture."

"We can centralize all our data models."

"With Looker, I have experienced benefits in terms of usability and shareability."

"The stability of Looker has been good since I have been using it. However, it depends on what components are being used."

"Looker is an extremely valuable product that can really transform your company's ability to use data to answer challenging questions."

"It is easier and quicker to find things in the database."

"From a developer's perspective, the way the functionality's being handled is great."

More Google Data Studio pros

Cons

"There was an issue with the incremental aggregation not working as indicated."

"The organization of the icons is not saved across users."

"The product was not able to meet our 10 second refresh requirements."

"Features related to visualization should continue to be improved."

"One thing is that Looker is not user-friendly to non-technical users."

"The main area of concern in Looker is probably related to blending the data from the different sources, including the data present internally in the company and on the cloud."

"There is a lot of customization that we needed/need to build ourselves. Other BI tools have more out of the box."

"It needs to be more user-friendly."

"Looker depends on the database components. For example, if you have a underperforming database, then you likely will have a poor performance experience."

"The product does not have documented material."

"This product is useful for non-technical users, who are able to use the interface to easily slice data. But for the admin users who are responsible for maintaining the schemas and files behind the scenes, it can easily become a chore, as there is a lot of manual work involved in defining the schemas of the connected database(s), as well as any refactored tables; the restrictive syntax also makes maintenance difficult."

More Google Data Studio cons

Pricing and Cost Advice

Information not available

"It's not cheap, but it's not expensive for big companies."

"The price of Looker usually depends on the solution's provider, but it is usually cheaper than the other products in the market. Looker is offered at different prices for different companies."

"I do not have to make any payments to use the solution."

"It is cheap."

"Looker is expensive and could be made better by reducing it."

See which vendors are best for you

Use our free recommendation engine to learn which Data Virtualization solutions are best for your needs.

See recommendations

894,668 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Healthcare Company

13%

Financial Services Firm

11%

Computer Software Company

10%

Manufacturing Company

10%

Financial Services Firm

14%

Retailer

Media Company

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	5
Midsize Enterprise	8
Large Enterprise	7

Questions from the Community

Ask a question

Earn 20 points

What needs improvement with Looker?

One thing is that Looker is not user-friendly to non-technical users. Someone with knowledge of Looker can understand it, but a person without any technical background finds it somewhat advanced or...

See all answers

What is your primary use case for Looker?

Looker serves as our main business intelligence reporting tool by creating dashboards and reports. We create interactive dashboards that help users understand the changes in data and the current tr...

See all answers

What advice do you have for others considering Looker?

My advice to others looking into using Looker is that if they are new users with some technical knowledge of SQL or Python, they can understand LookML code or use the explore tab to drag and drop t...

See all answers

Comparisons

SAP BusinessObjects Business Intelligence vs AtScale Adaptive Analytics (A3)

Compared 12% of the time

Collibra Platform vs AtScale Adaptive Analytics (A3)

Compared 12% of the time

Kyvos vs AtScale Adaptive Analytics (A3)

Compared 9% of the time

Dremio vs AtScale Adaptive Analytics (A3)

Compared 9% of the time

SAP HANA vs AtScale Adaptive Analytics (A3)

Compared 8% of the time

More AtScale Adaptive Analytics (A3) Competitors

Tableau Enterprise vs Google Data Studio

Compared 11% of the time

Microsoft Power BI vs Google Data Studio

Compared 11% of the time

MicroStrategy vs Google Data Studio

Compared 7% of the time

ThoughtSpot vs Google Data Studio

Compared 7% of the time

Databricks vs Google Data Studio

Compared 7% of the time

More Google Data Studio Competitors

Product Reports

Buyer's Guide

BI (Business Intelligence) Tools

April 2026

Download AtScale Adaptive Analytics (A3) product report

Buyer's Guide

Google Data Studio

May 2026

Download Google Data Studio product report

Also Known As

AtScale, AtScale Intelligence Platform

Looker

Overview

AtScale Adaptive Analytics (A3) revolutionizes data analysis for businesses by delivering powerful insights and facilitating informed decision-making. Its unique architecture optimizes operational efficiency and enhances data-driven strategies.

AtScale Adaptive Analytics (A3) integrates seamlessly with existing data environments, providing a modern and flexible approach to analytics. It allows organizations to access data from multiple sources without duplicating or moving it, ensuring efficiency and reducing costs. Advanced analytics capabilities enable enterprises to generate insights at scale, delivering actionable intelligence quickly. Its robust security features protect sensitive information, ensuring compliance and trust.

What are the key features of AtScale Adaptive Analytics (A3)?

Seamless Data Integration: Connects with diverse data environments without relocation.
High-Performance Data Virtualization: Enables rapid access and transformation of data across platforms.
Advanced Analytical Functions: Offers scalable insights using sophisticated analytical methods.
Centralized Security and Governance: Protects data integrity and complies with industry standards.
Cloud Agility & Scalability: Adapts to cloud or on-premises systems to meet growing business demands.

What benefits should users look for in reviews?

Cost Efficiency: Reduces data duplication costs and lowers operational expenses.
Enhanced Decision Making: Quickly delivers actionable insights for strategic decisions.
Improved Security Compliance: Maintains data privacy and meets regulatory requirements.
Versatile Analytics Capabilities: Supports complex data queries and enhances analytical output.
Flexibility in Deployment: Offers adaptable solutions compatible with cloud and traditional infrastructures.

AtScale Adaptive Analytics (A3) is widely implemented across industries like finance, healthcare, and retail where large-scale, secure, and insightful data analysis is paramount. Financial institutions benefit from its ability to adapt to changing regulations while healthcare organizations leverage it for detailed patient data analysis. Retailers use AtScale Adaptive Analytics (A3) to understand consumer behavior, enhancing customer experiences and inventory management. Its adaptability allows industry-specific customization, ensuring tailored analytics solutions.

AtScale

Google Data Studio enables seamless integration with Google's ecosystem, enhancing data visualization with Looker's capabilities. Its semantic layer and real-time insights support efficient dashboard creation and sharing.

Google Data Studio offers comprehensive data management through LookML, allowing custom data modeling with minimal training. Its centralized data management facilitates dashboard creation for non-technical employees. Users benefit from real-time insights and advanced analytics, along with automated reporting that reduces workload. Although it offers customization and data-level security, areas like visualization flexibility and large dataset performance need improvement. Challenges include handling complex filters, limited chart types, and the absence of multi-sheet options.

What are the key features of Google Data Studio?

Seamless Google Integration: Direct connection with Google tools for enhanced data processes.
Looker Visualization Capabilities: Robust visualization with Looker's advanced features.
LookML Data Modeling: Custom data models created with minimal learning curve.
Real-Time Insights: Automated reporting for up-to-date analytics.
Data-Level Security: Secure handling of sensitive information.

What benefits and ROI can users expect?

Efficient Dashboard Sharing: Non-technical users can easily create and share insights.
Reduced Workload: Automated features cut down manual reporting tasks.
Advanced Analytics: Enhanced decision-making through detailed analytics capabilities.
Community Support: Access to a stable community for assistance and knowledge sharing.

Google Data Studio is implemented in industries like real estate, sales, and marketing for creating operational reports and understanding trends. It helps organizations visualize data for customer behavior analytics, supporting developers in managing integrations and data governance efficiently.

Google

Sample Customers

Rakuten, TD Bank, Aetna, Glaxo-Smith Kline, Biogen, Toyota, Tyson

Yahoo!, Etsy, Kohler, Hipcamp, Hubspot, Kickstarter, Venmo, Dollar Shave Club, 600+ customer

We monitor all Data Virtualization reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.